Open AccessResearch on Classroom Teaching Behavior Analysis and Evaluation System Based on Deep Learning Face Recognition Technology
Author(s) -
Chengze Ma,
Ping Yang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1992/3/032040
Subject(s) - face (sociological concept) , computer science , deep learning , facial recognition system , face to face , quality (philosophy) , mathematics education , teaching method , artificial intelligence , psychology , pattern recognition (psychology) , social science , philosophy , epistemology , sociology
With the continuous enrichment of educational resources, how to analyze and evaluate classroom teaching behavior has become one of the important indicators to measure teaching quality. Based on this, this article builds a classroom teaching behavior analysis and evaluation system based on deep learning face recognition technology, and conducts professional course classroom behavior analysis, from three perspectives: the concentration of the student’s side face, the concentration of the student’s head down, and the concentration of the eyes. Make judgments. The experimental results show that face recognition technology based on deep learning can effectively judge students’ classroom behavior and facilitate teaching management and implementation.